Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Longer Life, Better Health?
Trends in health expectancy in New Zealand,
1996–2006
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
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Citation
Ministry of Health and Statistics New Zealand (2009). Longer life, better health? Trends in health
expectancy in New Zealand 1996–2006. Wellington: Statistics New Zealand
Published in July 2009 by
Statistics New Zealand
Tatauranga Aotearoa
Wellington, New Zealand
_____________________
ISBN 978-0-478-31589-9 (online)
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Foreword
Our health system aims, above all else, to improve the health of our population. So to
manage this complex system effectively and efficiently, we need to be able to measure
population health. Health expectancy – a generalisation of life expectancy to include nonfatal as well as fatal health outcomes – provides just such a metric.
Health expectancy, in the form of independent life expectancy (the expectation of life free of
functional limitation requiring assistance), has been used by the Ministry of Health as a
summary measure of the performance of our health system for some years. Since 2003, this
metric has served as the peak health indicator in documents such as the Ministry’s
Statement of Intent and its Health and Independence Report, as well as the Ministry of
Social Development’s overarching Social Report.
Yet opportunities remain for wider application of health expectancy indicators within the
health policy space, and methods for constructing these indicators are not yet fully
standardised. Accordingly, in 2008 the Ministry of Health and Statistics New Zealand
produced a joint discussion paper Health Expectancy: Toward Tier 1 Official Statistic Status,
to seek advice on this issue. We are grateful to all those individuals and organisations who
responded to this discussion paper with useful suggestions and constructive criticism.
Based on this consultation, the Ministry and Statistics NZ have now produced the current
report Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006.
This report sets out standard definitions and methods for health expectancy indicators, and
makes recommendations as to the appropriate indicator for most health policy applications.
The report also provides final estimates for health expectancy over the past decade. While it
is pleasing to note that all health expectancy indicators have improved, some expansion of
morbidity has also occurred. This has clear implications for health policy, especially in the
context of an ageing population.
This report will now provide a key input into Statistics NZ’s formal process for conferring Tier
1 official statistic status on health expectancy as a headline health indicator. Whatever the
outcome of this process, this report will help policy makers, planners, and funders in the
health sector make better use of these indicators for the assessment and management of
health system performance – and so contribute to better informed health policy, wiser
investment decisions, and consequently better health for us all.
Stephen McKernan
Director-General of Health
Geoff Bascand
Government Statistician
3
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Acknowledgements
This report was written by Martin Tobias, Li-Chia Yeh and Stephen Salzano (Ministry of
Health) and Conal Smith, Jade Pinkerton and Barb Lash (Statistics NZ).
The authors gratefully acknowledge valuable input from peer reviewers of this report and
respondents to the discussion paper this report is based on.
4
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Contents
Foreword ................................................................................................................................. 3
Acknowledgements ................................................................................................................. 4
Contents.................................................................................................................................. 5
Executive summary ................................................................................................................. 6
Introduction.......................................................................................................................... 6
Data sources and methods ................................................................................................. 6
Findings ............................................................................................................................... 7
Discussion ........................................................................................................................... 8
Recommendations .............................................................................................................. 9
Introduction ........................................................................................................................... 10
Why measure and monitor health expectancy? ................................................................ 10
What to measure? A taxonomy of health expectancies .................................................... 11
Health state expectancies ................................................................................................. 12
Health-adjusted life expectancy ........................................................................................ 13
Data sources and methods ................................................................................................... 16
Mortality ............................................................................................................................. 16
Non-fatal health states ...................................................................................................... 16
Populations........................................................................................................................ 16
Estimation of health expectancies ..................................................................................... 16
Health expectancy in 2006 .................................................................................................... 17
Total population ................................................................................................................. 17
Mäori and non-Mäori comparison ...................................................................................... 19
Trends in health expectancy, 1996–2006 ............................................................................. 23
Evidence for compression or expansion of morbidity ........................................................ 24
Discussion............................................................................................................................. 27
Strengths and limitations of health expectancy as an indicator ......................................... 27
Choice of health expectancy indicator ............................................................................... 29
Recommendations ............................................................................................................ 30
References............................................................................................................................ 32
Appendix 1 ............................................................................................................................ 34
Method for calculating health expectancies using Sullivan’s observed prevalence
approach ........................................................................................................................... 34
Appendix 2 ............................................................................................................................ 37
Summary of feedback from consultation on discussion document.................................... 37
5
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Executive summary
Introduction
To monitor and improve the performance of the health system as a whole, we need a
summary measure of population health – one that integrates both fatal (quantity of life) and
non-fatal (quality of life) outcomes. Health expectancy – a generalisation of life expectancy
to include time lived in different non-fatal health states defined by level of functioning –
provides just such a measure.
Two types of health expectancy indicators can be distinguished:
• health state expectancies
• health adjusted life expectancy.
Health state expectancies use defined functional limitation thresholds to categorise personyears into different health states. Based on data collected in Statistics NZ’s post-censal
disability survey (as well as mortality and population data), three health state expectancies
may be defined:
• limitation-free life expectancy (LFLE) – the number of years expected to be lived free
of any functional limitation
• independent life expectancy (ILE) – the number of years expected to be lived free of
functional limitation needing assistance
• active life expectancy (ALE) – the number of years expected to be lived free of
functional limitation needing daily assistance.
Health adjusted life expectancy (or healthy life expectancy, HLE) is based on continuous
weighting of non-fatal health states relative to full health, rather than categorical functional
limitation thresholds. So HLE can be defined as the equivalent number of years of full health
that a person can expect to live.
Independent life expectancy has been used as the ‘peak’ health indicator in the Ministry of
Health’s Statement of Intent and Health and Independence Report, and The Social Report
(Ministry of Social Development). However, understanding of these indicators is limited and
methods for their calculation have not been fully standardised. This led to a joint project
between the Ministry of Health and Statistics NZ to seek advice on these issues. A
discussion paper was produced and used as the basis for wide consultation in late 2008.
The current report builds on this consultation to:
• set out standard definitions and methods for health expectancy indicator construction
• provide final estimates for health expectancies in 2006, and trends from 1996 to 2006
• make recommendations for the choice of health expectancy indicators, and the
reporting, international benchmarking, and evaluation of the use and usefulness of
these indicators
• support consideration of Tier 1 official statistic status for the health expectancy
metric.
Data sources and methods
Abridged life tables for 1995–97, 2000–02 and 2005–07 were provided by Statistics NZ.
Estimates of the prevalence of non-fatal health states stratified by level of functional
limitation, age, sex, and (2006 only) Mäori-non-Māori ethnicity, were extracted from the
corresponding post-censal disability surveys fielded by Statistics NZ.
6
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Health expectancies were calculated by the standard method recommended by the
International Network for Health Expectancy (REVES).
Findings
Because ILE is recommended as the health expectancy indicator of choice for most policy
purposes (see ‘Recommendations’ below), only findings for LE and ILE are summarised
here.
Over the past decade, life expectancy at birth for New Zealand males increased steadily,
and at a faster rate than for females, increasing from 74.4 years in 1996 to 78.0 years in
2006 – a gain of 3.6 years. The corresponding increase for females was 2.6 years, from 79.6
years in 1996 to 82.2 years in 2006. So the gender gap in life expectancy decreased from
5.2 years to 4.2 years over the decade.
Independent life expectancy at birth increased from 64.8 years to 67.4 years over the
decade for males, an increase of 2.6 years. So 72 percent (2.6 / 3.6) of the life years gained
by males were lived in good health (ie independently). The corresponding increase for
females was 1.7 years, from 67.5 years in 1996 to 69.2 years in 2006. So 65 percent (1.7 /
2.6) of the life years gained by females were lived in good health.
While independent life expectancy increased, and at least two thirds of the years of life
gained were years of good health, morbidity still expanded (because life expectancy
increased even faster). Years lived in poor health (defined as states of dependency)
increased by 1.0 years (or 1.3 percent of life expectancy) for males and 0.9 years (or 1.1
percent of life expectancy) for females.
The surveys used to estimate prevalence of functional limitation by support need level were
insufficiently powered statistically to permit analysis of health expectancy trends by ethnicity.
However, estimates were produced for Mäori and non-Māori in 2006. The current gap in life
expectancy at birth (pooling genders) is 8.3 years and the corresponding gap in independent
life expectancy is 6.5 years. Thus Mäori can expect to live shorter lives and fewer years
independently than non-Māori. However, Mäori can also expect to live fewer years
dependently (9.7 years versus 11.8 years), and the lifetime proportion lived independently is
approximately the same for both ethnic groups (around 86 percent).
This analysis of trends and inequalities in health and life expectancy in New Zealand from
1996 to 2006 illustrates the potential value of such information for health policy. That both LE
and ILE have increased substantively over the decade indicates good health system
performance, although benchmarking internationally would be necessary to contextualise
this finding. However, unacceptable inequality remains between Mäori and non-Māori ethnic
groups (although this gap narrowed over the decade, at least for life expectancy). Also, while
over two thirds of the survival gain experienced by the population as a whole were years of
good health, time spent in dependent health states (‘morbidity’) also expanded.
This suggests that increased investment in long-term but low fatality conditions may be
needed to manage this growing burden. To make such reprioritisation decisions will require
drilling down (to the extent possible) from the summary health expectancy indicator to
identify the specific health conditions and interventions that will yield the best value for
money. Ongoing monitoring of health expectancy will then evaluate the extent to which
compression of morbidity has been achieved over the longer term. This is a goal of critical
importance for sustainability of the health system as the structural ageing of the population
accelerates over the next 20 years.
7
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Discussion
Strengths and weaknesses
The strengths of the health expectancy metric as a whole-of-system outcome indicator are
its robustness, transparency, comprehensiveness, and low cost.
Limitations include:
• reliance on functional limitation as the measure of non-fatal health states
•
limited ability to drill down to specific subsystem components or decompose
estimates for subnational regions or population groups
•
difficulties in attribution of changes in these measures to changes in health care
subsystem performance
•
potential confusion between functional limitation as a health outcome and disability
as a minority rights issue.
Choice of indicator
Health state expectancies have two major disadvantages: the health of the population
cannot be summarised in a single number (instead, three are required if the indicators
discussed here are used), and measurement is susceptible to drift in the threshold used to
define the indicators (eg daily versus non-daily dependency). On the other hand, a set of
health state expectancies provides more information than a single health-adjusted life
expectancy indicator.
HLE (as a health-adjusted life expectancy indicator) overcomes these limitations, but
introduces new ones – namely, the validity of the preference weights (health state values) for
the non-fatal health states, and the more complex interpretation of the indicator as a
transformation rather than a decomposition of life expectancy. Also, the preference weights
are liable to be misunderstood as valuations of people’s lives.
If only a single indicator is to be selected – for reasons of policy focus and ease of use –
then ILE may be the best choice. Firstly, ILE does not require valuation of non-fatal health
states. Secondly, the functional limitation threshold used in the construction of ILE –
dependency – is both stable and meaningful in a policy sense. Finally, as a decomposition
rather than a transformation of LE, the LE-ILE difference and the ILE:LE ratio are directly
interpretable.
Whichever health expectancy indicator (or set of indicators) is chosen, they need to form
part of a ‘balanced scorecard’. Summary measures of population health such as health
expectancy should be seen as only one input into evidence-informed health policy, and need
to be supported by more detailed cause- and service-specific indicators. Nevertheless, this
metric can provide a powerful assessment of overall health system performance and may be
particularly valuable now, as we enter an era of rapid structural ageing of the population.
8
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Recommendations
1. Health expectancy should continue to be monitored as the ‘peak’ health system
outcome indicator, and reported in the Health and Independence Report (Ministry of
Health), The Social Report (Ministry of Social Development) and similar publications.
2. Only a single health expectancy indicator should be routinely reported and
monitored: independent life expectancy (ILE).
3. This indicator (ILE) should be considered for Tier 1 status1 as part of New Zealand’s
official statistics.
4. ILE should be monitored and reported five-yearly, in the second year following each
Census of Population and Dwellings.
5. Estimates should be produced (nationally) for both the total New Zealand and Mäori
populations.
6. The sources of data should continue to be the official life tables and the post-censal
disability survey (or equivalent survey), both provided by Statistics NZ.
7. Production of the ILE estimates from these data, using standard methods (ie those
set out in Appendix 1 of this report) as per the requirements for Tier 1 statistics, and
the reporting and interpretation of these estimates, should be the responsibility of the
Ministry of Health.
8. The Ministry of Health and Statistics NZ and should undertake further joint work to
develop methods for producing:
• projections of ILE
• subnational estimates of ILE (ie regional, ethnic, socio-economic group)
• improved ILE estimates and projections for Mäori.
9. Use and usefulness of ILE as a summary measure of population health, to inform the
Ministry of Health’s long-term planning as well as broader social policy, should be
periodically evaluated.
10. New Zealand, through the Ministry of Health, should participate actively in attempts
by the International Network on Health Expectancy (REVES) and other international
organisations to improve the cross-country comparability and international
benchmarking of health expectancy estimates.
1
The intent of introducing the concept of Tier 1 statistics is to ensure that the important statistics that
departments use to advise and inform Ministers, and which are of broad public interest, are of a consistently
high quality and integrity.
9
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Introduction
Why measure and monitor health expectancy?
The health policy debate in New Zealand, as in other countries, has traditionally emphasised
measures of population health based on mortality (including standardised mortality ratios,
years of life lost, and life expectancy). This emphasis has been at the expense of more
broadly based population health measures that take into account non-fatal as well as fatal
health outcomes. To some extent this situation reflects the longstanding availability of
reliable, complete and comparable mortality records. Yet reliance on mortality as the sole
population health outcome worthy of measurement can seriously distort public health policy
and bias resource allocation in ways that may well be sub-optimal from a societal
perspective.
Such a limited view of population health is no longer necessary with the availability of valid
and reliable survey instruments to measure non-fatal health states (World Health
Organization 2002). The International Classification of Functioning (ICF) (World Health
Organization 2001) defines non-fatal health states by level of functioning across a range of
health domains (including vision, hearing, communication, cognition, affect, pain, mobility
and dexterity) and health-related domains (including self-care, instrumental routines, and
social functioning).
Survey data describing the distribution of the population by level of functioning (ie across a
set of non-fatal health states) can be combined with mortality data (in the form of a life table)
to produce a summary measure of population health: one that extends the range of our
understanding from life expectancy to health expectancy (Murray et al 2002).
Health expectancy indicators have the potential to transform the health policy debate in the
developed world from a narrow preoccupation with the extension of life to a broader concern
with population health gain (World Health Organization 1997, Romieu and Robine 1997).
Such measures are particularly useful for monitoring the health of ageing populations and
can help guide resource allocation decisions. These measures can also serve to bring equity
objectives – whether between generations, genders, social classes, ethnic groups or regions
– more sharply into focus.
Monitoring population health (in terms of both level and distribution) is essential for
assessing the performance of the health system. As a summary measure of population
health that integrates both fatal and non-fatal health outcomes, health expectancy plays a
crucial role in this process by providing an overall outcome measure of system performance.
Indeed, the health expectancy metric reflects the performance not only of the health sector
itself, but of all sectors whose actions contribute substantively to population health
outcomes. Therefore, policymakers, advisors and researchers across the social policy
spectrum may find this indicator useful when reflecting on their own contribution – potential
or realised – to the achievement of population health gain and the reduction of health
inequalities.
Given this capability, health expectancy has been accepted by the Ministry of Health as a
key whole-of-system outcome indicator, much as has been the case in the US (Molla et al
2001), the European Union (European Health Expectancy Monitoring Unit 2007) and (to a
lesser extent) the UK (Parliamentary Office of Science and Technology 2006). Since 2003,
the Ministry of Health has reported on health expectancy (in the form of independent life
expectancy) as a ‘headline’ health indicator in both the Statement of Intent (Ministry of
Health 2003b et seq) and the Health and Independence Report (Ministry of Health 2003a et
seq). Also since 2003, independent life expectancy has been reported as the ‘peak’ health
10
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
indicator in the 'Health' chapter of The Social Report (Ministry of Social Development 2003 et
seq).
These reports employ a pyramidal health indicator framework, with health expectancy
forming the peak of the pyramid (figure 1). At the next level, this integrated measure of
health is decomposed into its two components – life expectancy and level of functioning,
aggregating fatal and non-fatal health outcomes respectively. The following level in turn
decomposes each of these major outcome categories into their major direct causes
(diseases and injuries). The next level attributes these proximal causes to biological and
behavioural risk and protective factors. The foundation of the pyramid is made up of the
distal social, cultural and environmental determinants of health.
Figure 1
Health Indicator Logic
Beyond its use as a key outcome indicator, the health expectancy construct has also been
applied, for example, in the long-term forecasting of public health expenditure (Tobias et al
2004, 2009). Research on social inequalities in health expectancy and on compression of
morbidity in New Zealand has also been carried out by Davis and colleagues (Davis et al
1999, Graham et al 2004).
What to measure? A taxonomy of health expectancies
Definition of health expectancies
The health expectancies reported in New Zealand are based (along with mortality and
population data) on self-reported level of functioning in a range of health and health-related
domains. These include the core domains identified in the World Health Organization’s
International Classification of Functioning (ICF) (Tobias and Blakey 2007).
Population estimates and mortality data are obtained from Statistics NZ’s official statistics
system. The data source for level of functioning has been the post-censal disability surveys
11
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
fielded by Statistics NZ in 1996, 2001 and 2006. Respondents in these surveys were asked
whether they experienced any difficulty and/or needed any assistance with various
dimensions of functioning, or with performing specified everyday activities, because of a
long-term condition or health problem. For children under 15 years (reported via proxy), a
broader definition was used which also included specific chronic conditions and education
support needs. Domains of functioning included in the surveys were:
• sensory (hearing, seeing)
• communication (speaking, making self understood by others)
• cognition (learning, remembering, intellectual functioning)
• affect (emotional and psychological functioning)
• physical mobility
• agility and dexterity
• self-care
• usual everyday activities (instrumental routines)
• socialising (mixing with others).
Respondents who indicated that they experienced difficulty or needed help with any of the
itemised functions or activities were considered to have a functional limitation. The limitation
had to be for a minimum of six months (or be expected to last for that time) and not be
eliminated through the use of simple corrective devices like eye glasses.
Classification of health expectancies
Two types of health expectancy indicators can be constructed from such data: health state
expectancies and health-adjusted life expectancy.
Health state expectancies
Health state expectancies are calculated using defined functional limitation thresholds to
categorise individuals into different health states. Three health state expectancies are
reported here. To construct these indicators, the threshold for functional limitation was set at
dependency: the need for assistance (from another person or a complex assistive device)
with everyday routines, either intermittently or continuously. Specifically, participants in the
post-censal disability surveys who acknowledged functional limitation(s) were classified into
three support need levels:
•
•
•
level 1 (low)
level 2 (moderate)
level 3 (high)
no need for assistance
assistance needed, but only intermittently
assistance needed on a daily basis.
Based on this framework, three health state expectancies can be identified: limitation-free
life expectancy (LFLE), independent life expectancy (ILE), and active life expectancy (ALE)
(box 1 and figure 1). Note that health state expectancies represent a decomposition of life
expectancy, so that the sum of the time spent in the different health states equals life
expectancy (at birth or any other age).
12
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Box 1 Health State Expectancies
Limitation-free life expectancy is the number of years, on average, that a person can
expect to live free of any functional limitation.
Independent life expectancy is the number of years, on average, that a person can expect
to live independently – that is, free of functional limitation needing assistance (whether
intermittently or on a daily basis).
Active life expectancy is the number of years, on average, that a person can expect to live
free of functional limitation needing daily assistance.
Figure 2
A Conceptual Model of Health State Expectancies
Level of
support
need
No functional
limitation
Level 1
Functional limitation
not requiring assistance
Level 2
Functional limitation
requiring non-daily
assistance
Level 3
Limitation-free
life expectancy
Independent life
expectancy
Active life
expectancy
Life
expectancy
Functional limitation
requiring daily
assistance
Health-adjusted life expectancy
Health-adjusted life expectancy (or healthy life expectancy, HLE) is based on continuous
weighting of non-fatal health states, rather than on categorical functional limitation thresholds
(as in health state expectancies).
The health states are weighted relative to the state of ‘full health’ (weight = 1). Therefore,
HLE can be seen as a transformation of life expectancy (rather than as a decomposition of
it), and has the advantage over health state expectancies that only a single indicator is
13
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
needed to describe the health status of the whole population. HLE may be defined as follows
in Box 2.
Box 2 Healthy Life Expectancy
Healthy life expectancy (or health-adjusted life expectancy) is the equivalent number of
years of full health, on average, that a person can expect to live.
The health state weights required for construction of HLE can be derived in two ways:
• through a health state valuation survey, in which the preferences of the
population for time spent in the different component health states (relative to full
health) are elicited
• by arbitrary assignment of weights.
In the absence of New Zealand health state valuation data, the latter method has been used
in this report, with equidistant weights of 0.75, 0.5 and 0.25 being assigned to the three
levels of functioning defined by the component health state expectancies (figure 3).
Figure 3
A Conceptual Model of Healthy Life Expectancy
No functional limitation
Functional limitation
not requiring assistance
Functional limitation
requiring non-daily
assistance
Life
expectancy
Functional
limitation
requiring daily
assistance
0.00
0.25
0.50
0.75
Health state weights
14
1.00
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Although the weights have been chosen for their mathematical properties rather than to
represent New Zealanders’ preferences for different states of health, the rank order of the
weights is likely to be the same. Given consistent rank ordering, HLE is not very sensitive to
the exact weights used, depending more on their relative sizes. Furthermore, the use of
arbitrary weights still allows estimation of trends in HLE, provided the weights are not
changed over time.
Alternatively, the arbitrary weights could be replaced in future by weights from a New
Zealand health state valuation survey, and the historical estimates recalculated using these
weights. The weights chosen are reasonably similar to those derived from a Dutch health
state valuation exercise (Stouthard et al 1997) and to those employed in the WHO’s Global
Burden of Disease Study (Mathers et al 2002).
From figures 2 and 3, it can be seen that the relationship between HLE, LE, and the health
state expectancies is given by:
HLE = LFLE + 0.75(ILE – LFLE) + 0.5 (ALE – ILE) + 0.25 (LE – ALE)
The variance of healthy life expectancy is given by:
Var(HLE) = 0.0625 x [Var(LFLE) + Var(ILE) + Var(ALE) + Var(LE)]
15
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Data sources and methods
Mortality
Abridged life tables for 1995–97, 2000–02 and 2005–07 for the total population and the
Mäori and non-Māori populations (by sex) were provided by Statistics NZ.
Mäori mortality rates for 1995–97 and 2000–02 were corrected for numerator-denominator
bias using New Zealand Census Mortality Study adjustors (Blakely et al 2007). Although
adjustors are not yet available for 2005–07, these have been close to 1.0 for all age groups
since 2000–02, so non-adjustment of the 2005–07 estimates should have little (if any) effect.
Non-fatal health states
Estimates of the prevalence of different health states, defined by level of functional limitation,
by sex, Mäori-non-Māori ethnicity and 10-year age group, were derived from the 1996, 2001
and 2006 post-censal Household Disability Surveys and companion surveys of residential
facilities fielded by Statistics NZ. The household and institutional surveys were designed to
allow pooling of data so that the distribution of the whole population across the set of health
states could be estimated.
Populations
Population denominators were the respective censal populations. The total ethnic group
concept of ethnicity was used. Ethnic analysis had to be restricted to Mäori and non-Māori,
because of the small numbers of Pacific and Asian respondents in the surveys.
Estimation of health expectancies
Abridged life tables incorporating non-fatal health state distributions were constructed for
each sex by ethnic group for each period using the observed prevalence method (Sullivan
1971). To do this, the empirical health state prevalence estimates by 10-year age group
were first smoothed using kernel smoothing (Wand and Jones 1994) to obtain estimates by
five-year age group. Confidence intervals around the health expectancy estimates were
calculated using standard formulae (see Appendix 1).
HLE was calculated from the component health state expectancies using the formula given
on page 15.
More detail on the method for calculating health expectancies is provided in the REVES
manual (Jagger 2006).
16
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Health expectancy in 2006
Total population
Health state expectancies
The expectations of life in 2006, with and without different levels of functional limitation, at
different ages (selected to represent the beginning of each stage of the lifecycle) are
summarised in table 1.
Table 1
Expectation of Life With and Without Functional Limitation (Years)
By gender, level of functional limitation, and lifecycle stage
2006
Male
Female
Exact age
0
15
25
45
65
0
15
25
45
65
Limitation-free (LFLE)
61.1
48.2
39.5
22.5
8.9
64.4
51.0
41.8
24.3
10.1
Independent (ILE)
67.4
53.9
44.7
26.6
11.2
69.2
55.3
45.8
27.6
11.9
Active (ALE)
74.8
60.7
51.3
32.5
15.5
78.4
64.1
54.4
35.2
17.5
Limited (LE –LFLE)
16.9
15.5
14.7
12.9
9.0
17.8
16.7
16.1
14.3
10.5
Dependent (LE – ILE)
10.6
9.8
9.5
8.7
6.8
13.0
12.4
12.1
11.0
8.7
(LE – ALE)
3.2
3.0
2.9
2.8
2.4
3.7
3.6
3.5
3.3
3.1
LE
78.0
63.7
54.2
35.3
18.0
82.2
67.7
58.0
38.6
20.6
LFLE/LE
78.3
75.6
72.8
63.6
49.6
78.4
75.3
72.1
62.9
49.1
ILE/LE
86.4
84.6
82.5
75.4
62.4
84.2
81.6
79.2
71.5
57.9
ALE/LE
LE = life expectancy
95.9
95.3
94.6
92.2
86.4
95.5
94.7
93.9
91.3
85.0
Severely dependent
Ratios (%)
Limitation-free life expectancy
Approximately 78 percent of life expectancy at birth in 2006 is expected to be lived free from
functional limitation (any level). This is 61.1 out of 78.0 years (78.3 percent) for males and
64.4 out of 82.2 years (78.4 percent) for females. Note that from age 65 onwards, only half
the remaining years of life are expected to be spent free of functional limitation – 49.6
percent for males and 49.1 percent for females.
Females enjoy a longer life expectancy than males (by 4.2 years in 2006). Females can in
fact expect to live 3.3 years longer than males free of any functional limitation, and 0.9 years
longer limited. These estimates are consistent with estimates for previous years (1996,
2001), which found that females can expect to live longer than males both limitation-free and
limited.
17
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Independent life expectancy
About 85 percent of life expectancy at birth is expected to be free from functional limitation
requiring assistance (dependency) in 2006. This is 67.4 out of 78.0 years (86.4 percent) for
males and 69.2 out of 82.2 years (84.2 percent) for females. Even at age 65, over half of
remaining life expectancy will be lived independently (both sexes): 62.4 percent for males
and 57.9 percent for females.
Females enjoy a longer expectation of independent life than males – 69.2 versus 67.4 years
in 2006, a difference of 1.8 years (versus 4.2 years for total life expectancy). However,
females can also expect to live longer in a dependent state – 13.0 versus 10.6 years, a
difference of 2.4 years. That is, out of the 4.2 year female life expectancy advantage in 2006,
1.8 years (43 percent) are years of good health and 2.4 years (57 percent) are years of poor
health.
Active life expectancy
Over 95 percent of life expectancy at birth in 2006 is expected to be lived free from
functional limitation requiring daily assistance – 74.8 out of 78.0 years (95.9 percent) for
males and 78.4 out of 82.2 years (95.5 percent) for females. So males can expect, on
average, to live for 3.2 years needing daily assistance with self-care, whereas females can
expect 3.7 years in this health state.
Healthy life expectancy
Health adjusted life expectancy at selected ages is tabulated below (table 2). Note that
differences between LE and HLE, and the ratio of HLE to LE, are also shown – even though
some authorities regard such calculations as inappropriate, seeing that HLE is a
transformation, not strictly speaking a decomposition, of LE.
Table 2
Healthy Life Expectancy at Selected Ages (Years)
By gender
2006
Male
Female
Exact age
0
15
25
45
65
0
15
25
45
65
HLE
70.3
56.6
47.4
29.2
13.4
73.5
59.5
50.0
31.4
15.1
LE
78.0
63.7
54.2
35.3
18.0
82.2
67.7
58.0
38.6
20.6
Diff
7.7
7.1
6.8
6.1
4.6
8.7
8.2
8.0
7.2
5.5
90.1
88.9
87.5
82.8
74.6
89.5
87.9
86.3
81.4
73.0
%
Table 2 shows that in 2006 males could expect to live 70.3 healthy-year equivalents from
birth, while females could expect 73.5 – a difference (favouring females) of 3.2 years. This
represents a ‘loss’ corresponding to 7.7 and 8.7 life years for males and females
respectively, as a result of time spent in states of being other than full health. In both
genders this ‘loss’ is equivalent to approximately 10 percent of life expectancy at birth.
Interestingly, the health advantage of females as estimated using this metric is 3.2 years of
healthy life, exactly one year less than the 4.2-year difference in total life years in 2006.
18
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Note that ‘healthy-year equivalents’ as defined using the HLE metric are not the same as
limitation-free years as defined using LFLE. So, for example, males aged 65 years in 2006
can expect 18.0 more years of life (on average), 13.4 more healthy-year equivalents, and 8.9
more years free of any functional limitation.
Precision of the estimates
The precision of health expectancy estimates is limited mainly by the sampling error in the
survey used to estimate the distribution of the population across the set of non-fatal health
states included in the metric (table 3).
Table 3
Standard Errors and 95 Percent Confidence Intervals (Years)
Life and health expectancies
2006
SE
LCI
UCI
male
0.29
60.5
61.7
female
0.29
63.8
65.0
ILEo
male
female
0.25
0.26
66.9
68.7
67.9
69.7
ALEo
male
female
0.16
0.17
74.5
78.1
75.1
78.8
HLEo
male
female
0.11
0.11
70.1
73.3
70.5
73.7
LEo
male
female
0.08
0.06
77.8
82.1
78.2
82.3
LFLEo
Table 3 shows that, given the current survey, the precision is likely to be adequate for most
purposes. For example, the width of the confidence interval for health expectancies at birth
is generally about one year or less (compared with approximately 0.3 years for life
expectancy). This should be sufficient to detect any epidemiologically meaningful change in
health expectancy over a five year period.
Mäori and non-Mäori comparison
Health expectancy estimates for Mäori and non-Mäori were produced in the same way as
described above for the total New Zealand population. Only the key results are shown
below, for expectancies at birth only (table 4 and figure 4).
Note that estimates could not be produced for the ethnic minorities (Pacific and Asian ethnic
groups) because of severe imprecision in the age-specific functional limitation rates. That is,
the post-censal Disability Survey is not powered sufficiently to produce estimates for these
ethnic groups.
19
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Table 4
Life and Health Expectancies at Birth (Years)
Mäori and non-Mäori populations
2006
LFLEo
%LE
ILEo
%LE
ALEo
%LE
HLEo
LEo
Non-Mäori
62.3
(78.9)
68.8
(87.2)
76.1
(96.3)
71.5
79.0
Mäori
56.8
(80.7)
62.0
(88.2)
67.6
(96.1)
64.2
70.4
Difference
5.5
7.3
8.6
Males
6.8
8.5
Females
Non-Mäori
65.7
(79.2)
70.4
(84.9)
79.5
(95.8)
74.6
83.0
Mäori
58.7
(78.2)
64.2
(85.6)
72.2
(96.2)
67.6
75.1
Difference
7.0
7.0
7.9
6.2
7.3
Figure 4
Health and Life Expectancies by Sex
Mäori and Non-Mäori
2006
90
80
Males
Years of life
Mäori
Non-Mäori
70
60
50
40
30
20
10
0
HLE0
ALE0
ILE0
LFLE0
Life expectancy
Note: HLE = healthy life expectancy; ALE = active life expectancy; ILE = independent life expectancy;
LFLE = limitation-free life expectancy; LE = life expectancy.
20
LE0
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Females
Years of life
90
80
Mäori
Non-Mäori
70
60
50
40
30
20
10
0
HLE
0
ALE
0
ILE
0
LFLE
0
LE
0
Life expectancy
Note: HLE = healthy life expectancy; ALE = active life expectancy; ILE = independent life expectancy;
LFLE = limitation-free life expectancy; LE = life expectancy.
Table 4 and figure 4 shows that Mäori life expectancy at birth is now approximately 70.4
years for males and 75.1 years for females, a gender gap of 4.7 years. About 79 percent is
lived free of any functional limitation (corresponding to 56.8 years for males and 58.7 years
for females), while approximately 87 percent is lived independently (corresponding to 62.0
years for males and 64.2 years for females). At present, Mäori males and females can
expect to live 64.2 and 67.6 healthy-year equivalents, respectively.
Table 4 also shows that Mäori life expectancy at birth is now approximately 8.3 years less
than non-Mäori (pooling genders), reflecting substantial improvement in survival for Mäori in
recent years, although the difference remains unacceptably large. Inequalities in health
expectancies are generally smaller than those in life expectancy on an absolute scale, but
similar on a relative scale. This finding reflects the complex interaction between survival and
functional limitation that determines health expectancy. Thus while Mäori health and life
expectancies are uniformly lower than non-Māori, the ratios of health to life expectancies for
each ethnic group are similar.
Note that the confidence intervals for the health expectancy estimates are (unsurprisingly)
wider for Mäori than non-Mäori (table 5). They are generally about twice as wide (that is,
health expectancy confidence intervals are typically ~2 years for Mäori compared to ~1 year
for non-Mäori). This should be borne in mind when interpreting the results.
21
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Table 5
Standard Errors and 95 Percent Confidence Intervals (Years)
Life and health expectancies by ethnicity
2006
LFLEo
ILEo
ALEo
Mäori
male
SE
0.51
LCI
55.8
UCI
57.8
female
0.53
57.7
59.8
Non-Mäori
male
0.34
61.7
63.0
female
0.34
65.1
66.4
Mäori
male
0.43
61.2
62.9
female
0.47
63.3
65.2
Non-Mäori
male
0.28
68.3
69.4
female
0.30
69.8
71.0
Mäori
Non-Mäori
HLEo
Mäori
Non-Mäori
LEo
Mäori
Non-Mäori
male
0.28
67.1
68.2
female
0.29
71.7
72.8
male
0.17
75.7
76.4
female
0.19
79.1
79.8
male
0.18
63.9
64.6
female
0.19
67.2
67.9
male
0.12
71.3
71.8
female
0.12
74.4
74.9
male
0.11
70.1
70.6
female
0.09
74.9
75.2
male
0.07
78.9
79.1
female
0.06
82.9
83.1
22
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Trends in health expectancy, 1996–2006
In principle, health expectancy estimates for 1996, 2001 and 2006 should be comparable, as
all are based on the same data definitions, methods and data sources (Statistics NZ
abridged life tables and the post-censal disability survey). However, minor variations in
definitions, methods, survey questionnaires and fielding did occur, which have reduced data
comparability – especially for the 2006 survey versus the earlier surveys. Also, the
uncertainty (imprecision) in the health expectancy estimates needs to be borne in mind when
interpreting the trends (95 percent confidence intervals are not shown in the table for clarity,
but can be seen on the figure). With these caveats, trends in the key indicators (health
expectancies at birth) are shown below (table 6 and figure 5). As we have only three time
points, formal statistical tests for trend have not been done.
Table 6
Health Expectancies at Birth (Years)
By period
Male
Female
Change 1996–2006
1996
2001
2006
1996
2001
2006
Male
Female
HLE0
67.2
68.1
70.3
70.9
72.0
73.5
3.1 (4.6%)
2.3 (3.2%)
ALE0
72.1
73.2
74.8
75.9
77.7
78.4
2.7 (3.7%)
2.5 (3.3%)
ILE0
64.7
64.8
67.4
67.5
68.5
69.2
2.7 (4.2%)
1.7 (2.5%)
LFLE0
57.8
57.9
61.1
60.5
60.9
64.4
3.3 (5.7%)
3.9 (6.4%)
LE0
74.4
76.3
78.0
79.6
81.1
82.2
3.6 (4.8%)
2.6 (3.3%)
Notes: HLE = healthy life expectancy; ALE = active life expectancy; ILE = independent life expectancy; LFLE =
limitation-free life expectancy; LE = life expectancy.
Figure 5
New Zealand Health and Life Expectancies at Birth by Sex
1996, 2001 and 2006
90
80
Males
Years of life
1996
2001
2006
70
60
50
40
30
20
10
0
HLE0
ALE0
ILE0
LFLE0
Life expectancy
Note: HLE = healthy life expectancy; ALE = active life expectancy; ILE = independent life expectancy;
LFLE = limitation-free life expectancy; LE = life expectancy.
23
LE0
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
90
80
Females
Years of life
1996
2001
2006
70
60
50
40
30
20
10
0
HLE0
ALE0
ILE0
LFLE0
LE0
Life expectancy
Note: HLE = healthy life expectancy; ALE = active life expectancy; ILE = independent life expectancy;
LFLE = limitation-free life expectancy; LE = life expectancy.
Trends in HLE, ALE and ILE appear consistent over time for females (but less so for males).
Among females, LE at birth increased by 1.5 years from 1996 to 2001 and 1.1 years from
2001 to 2006. ILE increased less but in a similar pattern, by 1.0 years from 1996 to 2001 and
0.7 years from 2001 to 2006. By contrast, LFLE was almost stable from 1996 to 2001
(increasing by only 0.5 years), then increased implausibly by 3.5 years from 2001 to 2006.
Among males, LE increased faster than among females, by 1.9 years from 1996 to 2001 and
1.7 years from 2001 to 2006. However, both LFLE and ILE show atypical trends among
males, remaining stable from 1996 to 2001 while increasing rapidly – by 3.2 and 2.6 years
respectively – from 2001 to 2006.
These discontinuities in the time series for LFLE (both sexes) and, to a lesser extent, ILE
(males only) reflect a similar discontinuity in the disability survey time series. This suggests
that a change occurred between 2001 and 2006 in people’s perceptions of, or propensity to
report, mild to moderate levels of functional limitation (Statistics NZ has ruled out statistical
artefact as a likely explanation). This discontinuity is less evident for level 3 functional
limitation – so the other HSE trends, and the HLE trend, are likely to be more robust. Most
probably the estimated trends in HSEs and HLE from 2001 to 2006 represent a combination
of real change and artefact and these trends should therefore be interpreted cautiously.
Note that trends for Mäori are even less reliable, given the wide confidence intervals around
the HSE and HLE estimates for Mäori in 1996 and 2001 (arising from the corresponding
disability surveys). So trends are presented here for the all-New Zealand population only.
Evidence for compression or expansion of morbidity
Depending on the relative rates of change in health expectancy and life expectancy,
‘morbidity’ (the burden of non-fatal health outcomes) may become compressed, stay in
dynamic equilibrium, or expand. Which trajectory is followed is a question of major health
policy significance, especially in the context of an ageing population.
The trajectory of population health may be defined on an absolute or relative scale. For
example, a decrease in the number of years lived with dependency (ie in health states
characterised by level 2 or 3 functional limitation) would constitute evidence of compression
in an absolute sense. Similarly, a decrease in the proportion (percentage) of the lifetime
spent in such health states would constitute evidence of compression in a relative sense.
24
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
The findings for the past decade are summarised below (figure 6). However, these findings
should be interpreted cautiously in view of concerns regarding the comparability of the 2006
survey to the earlier surveys (described above).
Figure 6
Years Lived in Different Health States
In years and as a percentage of life expectancy
1996 and 2006
Years lived
10
9
1996
10.6%
8
7
6
11.3%
2006
9.9%
9.3%
9.5%
8.8%
8.1%
5.8%
5
4
4.6%
4.5%
4.1%
3
3.1%
2
1
0
level 1
level 2
level 3
level 1
level 2
level 3
Support need level
Male
Female
Note: Y axis shows years lived in each health state; percentage above bars shows proportion of life expectancy lived
in each health state.
The trajectory varies depending on the non-fatal health states included in the metric. For
females, level 1 morbidity (functional limitation) compressed on both absolute and relative
scales, while level 2 morbidity expanded and level 3 morbidity remained stable (dynamic
equilibrium). For males, level 1 morbidity again compressed, as for females. However, level
2 morbidity remained stable, while level 3 morbidity expanded.
Using dependency (ie level 2 + level 3 functional limitation) as the threshold for inclusion of
non-fatal health states in the indicator, morbidity expanded for both genders on both
absolute and relative scales: by 1.0 years or 1.3 percent of life expectancy for males and 0.9
years or 1.1 percent of life expectancy for females. Although these expansions appear
similar, note that the male expansion was comprised of level 3 health states while the female
expansion involved mainly level 2 health states. Again, however, the caveat stated above
regarding unexplained discontinuities in the post-censal survey time series should be borne
in mind.
Conclusions
Over the past decade, life expectancy at birth for New Zealand males increased steadily,
and at a faster rate than for females, increasing from 74.4 years in 1996 to 78.0 years in
2006 – a gain of 3.6 years. The corresponding increase for females was 2.6 years, from 79.6
years in 1996 to 82.2 years in 2006. So the gender gap in life expectancy decreased from
5.2 years to 4.2 years over the decade.
Independent life expectancy at birth increased from 64.8 years to 67.4 years over the
decade for males, an increase of 2.6 years. So 72 percent (2.6 / 3.6) of the life years gained
by males were lived in good health (ie independently). The corresponding increase for
females was 1.7 years, from 67.5 years in 1996 to 69.2 years in 2006. So 65 percent (1.7 /
2.6) of the life years gained by females were lived in good health. While independent life
expectancy increased, and at least two thirds of the years of life gained were years of good
25
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
health, morbidity still expanded (because life expectancy increased even faster). Years lived
in poor health (defined as states of dependency) increased by 1.0 years (or 1.3 percent of
life expectancy) for males and 0.9 years (or 1.1 percent of life expectancy) for females.
However, the reliability of these estimates is limited, for reasons stated above.
The surveys used to estimate prevalence of functional limitation by support need level were
insufficiently powered statistically to permit analysis of health expectancy trends by ethnicity.
However, estimates were produced for Mäori and non-Māori in 2006. The current gap in life
expectancy at birth (pooling genders) is 8.3 years and the corresponding gap in independent
life expectancy is 6.5 years. Thus Mäori can expect to live shorter lives and fewer years
independently than non-Māori. However, Mäori can also expect to live fewer years
dependently (9.7 years versus 11.8 years), and the lifetime proportion lived independently is
approximately the same for both ethnic groups (~86 percent).
This analysis of trends and inequalities in health and life expectancy in New Zealand from
1996 to 2006 illustrates the potential value of such information for health policy. That both LE
and ILE have increased substantively over the decade indicates good health system
performance, although benchmarking internationally would be necessary to contextualise
this finding. However, unacceptable inequality remains between Mäori and non-Māori ethnic
groups (although this gap narrowed over the decade, at least for life expectancy). Also, while
over two thirds of the survival gain experienced by the population as a whole were years of
good health, time spent in dependent health states (‘morbidity’) also expanded.
This suggests that increased investment in mental health and other long-term but low-fatality
conditions may be needed to manage this growing burden. To make such reprioritisation
decisions will require drilling down (to the extent possible) from the summary health
expectancy indicator to identify the specific health conditions and interventions that will yield
the best value for money. Ongoing monitoring of health expectancy will then enable us to
evaluate the extent to which compression of morbidity has been achieved over the longer
term – a goal of critical importance for sustainability of the health system as the structural
ageing of the population accelerates over the next 20 years.
26
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Discussion
Strengths and limitations of health expectancy as an indicator
Strengths
New Zealand is fortunate in having both high quality vital statistics (based on a five-yearly
population census and full registration of deaths) and a population-based, post-censal
disability survey (covering people of all ages living in both private dwellings and in residential
institutions). Thus the necessary information infrastructure to measure and regularly monitor
health expectancy already exists, and the additional cost of combining mortality and
functional limitation rates to generate these metrics is negligible.
Measurement and monitoring of population health (level and distribution) is an essential
ingredient of national health system performance assessment, and health expectancy is
perhaps better suited to this task than any other available (or even theoretical) measure
(WHO 2000).
An international network, the International Health Expectancy Network (known by its French
acronym REVES), has been operating for almost quarter of a century. It has achieved some
success in standardising definitions and methods so that international comparability of health
expectancy estimates is slowly improving. More and more countries and intergovernmental
organisations (eg the EU) are using these measures as headline (summary) indicators of
health system performance.
Yet these indicators are still subject to a number of technical and conceptual challenges as
outlined below.
Limitations
Measurement of non-fatal health states
Measurement of non-fatal health states depends on serial surveys of the population,
currently the post-censal disability survey fielded by Statistics NZ. Based on a recent
consultation on the future of this survey carried out by Statistics NZ, sustainability of the
necessary health state data seems assured – either through continuance of this survey or
inclusion of suitable items in the General Social Survey. Similar data could also be derived
from the New Zealand Health Survey operated by the Ministry of Health. Equivalence of the
data that could be collected in these surveys to that collected via the existing post-censal
disability survey would need to be demonstrated (especially with regard to health state
prevalence estimates disaggregated by support need level).
Valuation of health states
For estimation of health adjusted life expectancy (HLE), non-fatal health states must not only
be described but also valued. The lack of preference weights for New Zealand is clearly a
limitation in this regard, forcing us to rely on weights chosen for their mathematical
properties (ie equidistant weights) rather than weights reflecting New Zealanders’
preferences for being in different health states. If HLE is to be used as an outcome indicator,
a process to generate and regularly (say 10-yearly) update preference-based weights would
be needed. This could involve a general population survey or a panel approach (eg focus
groups of health workers, patients, family members, and/or politicians) (Stouthard et al
2000). However, whether HLE should be included at all in the indicator set is problematic, as
discussed below.
27
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Lack of longitudinal functional limitation data
Because we have no source of longitudinal data on non-fatal health states, health
expectancies can be estimated only by Sullivan’s observed prevalence method rather than
using multi-state life-table methods. Sullivan’s method is poorly responsive to recent
changes in population health, because of the inertia inherent in observed prevalence (which
is a stock variable and so depends on past as well as current flows). However, Mathers and
Robine (1997) have shown that this limitation may not be substantive provided population
health status changes only slowly and relatively smoothly, as indeed appears to be the case
in a developed country like New Zealand. More recently, Imai and Soneji (2007) have
provided for the first time a formal proof of the Sullivan method and confirmed its fitness for
purpose.
Reliance on self-report (for functional limitation)
Self-reports of functional limitation are subject to variation in norms and expectations
between cultural groups and over time. This reliance is typically most problematic for mild
rather than moderate or severe functional limitation thresholds, as appears to have been the
case in the 2006 post-censal survey compared with earlier surveys. Use of calibrators may
increase the robustness of self-reported data in future (WHO 2003), but it is unlikely that a
fully satisfactory solution to this inherent limitation will ever be found. Substitution of
objective tests for self-report is not practical in the context of a regular, relatively large
population-based survey. Nor are objective tests available for all health states (eg chronic
pain syndromes).
Limited ability to ‘drill down’ and undergo additive decomposition
The contribution of different causes (diseases, injuries, risk factors) to health expectancy can
be quantified by constructing cause-deleted health expectancies (Murray et al 2002), but the
contributions so obtained cannot be added across causes (since any death or non-fatal
health state is multi-causal). Methods for estimating the contributions of different diseases
and risk factors to health expectancy, based on regression modelling, have been developed
(Nusselder 2004, Rasulo 2007). However, the causal data collected in the current survey (or
any survey) is necessarily limited, so restricting our ability to ‘drill down’ to the level of
specific causes or cause groups. This restricted ability to ‘drill down’ from the high-level
summary measure to specific causes and interventions (eg specific health services) limits
the policy value of the health expectancy metric.
Limited decomposability
As well as limited ability to drill down by cause, decomposability by region or population
subgroup (eg ethnic group or social class) is also limited. In this case, the limitation is
imposed by sampling error in the survey component. In particular, ethnic analyses may have
to be confined to Mäori and non-Mäori only, with no reliable estimates being possible for
Pacific or Asian peoples. One solution might be to estimate partial rather than full health
expectancies for these ethnic groups (eg covering the age range from birth to 85 years only
– the main limitation is small numbers of Pacific or Asian respondents in older age groups).
Small domain estimation techniques could also be used to model the data for smaller ethnic
groups or regions, but can never be as robust as empirical estimates.
Moreover, decomposability by time period is also necessarily limited, both by the five-yearly
frequency of the survey component and by the slowness of possible change in the health
status of the population itself. Hence, more frequent updates than five-yearly are not
realistically possible, and are also unnecessary.
Narrow conceptualisation of health
A more fundamental limitation of health expectancy as an indicator of population health is
the arguably narrow conceptualisation of non-fatal health states as functional limitations,
ignoring other dimensions of wellbeing such as happiness, spirituality and ‘quality of life’.
28
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
This reductionist philosophy – sometimes described as a ‘biomedical model’ – may also be
limited in terms of its cross-cultural relevance.
Also of cultural relevance is that health expectancy explicitly locates health as an individual
attribute, with the population indicator being simply an aggregation of the estimates for
atomised individuals. This view contrasts with other cultural perspectives of health, which
view health more as a shared attribute of a family or local community, rather than relating
solely to individuals. However, no attempt has yet been made to incorporate such views
quantitatively into the aggregation method for health expectancy.
Attribution
A criticism sometimes raised against health expectancy as an outcome measure for the
health system is that it casts its net too wide – health expectancy is affected by factors
beyond health care. However, the boundaries of the health system extend beyond clinical
care. It is generally accepted that an objective of the health system is to improve the level
and distribution of population health. This does not mean that, in interpreting trends in health
expectancy (or in inequalities between social groups in health expectancy), changes in
macroeconomic performance, income distribution, labour market performance and similar
social variables should not be taken into account.
Health expectancy is a summary measure, reflective of whole-of-system performance.
Different indicators are needed to measure outcomes of specific health services (eg cancer
survival). Yet simply adding up all these service-specific indicators will not reveal whether
the health system as a whole is performing better or worse, or whether gaps between ethnic
or income groups are narrowing or widening. Both whole-of-system and service-specific
indicators are needed.
Ethics
Health expectancy is sometimes misunderstood as applying a narrow biomedical model to
the construct of disability. This is not the case. These indicators capture non-fatal health
states in terms of functional limitation – a concept related to impairment rather than disability.
Internationally, this distinction between ‘impairment’ and ‘disability’ is sometimes not drawn,
leading to semantic confusion.
While impairment often underlies disability, the two constructs are not necessarily closely
related. Furthermore, the majority of health states associated with functional limitation
involve older people who have developed multiple comorbid chronic diseases. By contrast,
the concern with disability as a human rights issue is often related to the social experience of
the young disabled, or those disabled from birth.
The health expectancy construct is in fact silent on disability as an issue of minority rights.
By contrast, by placing functional limitation at the centre of health (along with survival), it
recognises such limitation as part of the universal experience of humankind.
Similar misunderstandings surround the valuation of health states required to construct HLE.
The weights assigned to different health states reflect preferences for time spent in one
health state rather than another. They are not valuations of people’s lives. Nevertheless, the
ease with which these preference weights are misunderstood is one of the reasons for not
using HLE as a health system performance indicator (see below).
Choice of health expectancy indicator
Despite these limitations, health expectancy measures have two major advantages: they are
relatively easy to measure and monitor, and they do integrate both fatal and non-fatal
outcomes into a single index or summary measure of health. Furthermore, the construction
29
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
of this composite indicator is reasonably simple and transparent, and the value choices
implicit in its design are at least clear. The question still remains as to whether to focus on
health state expectancies or health-adjusted life expectancy as the preferred way of
summarising the health status of a nation or population.
Health state expectancies have two major disadvantages: the health of the population
cannot be summarised in a single number (instead, three are required if the indicators
discussed here are used), and measurement is susceptible to drift in the threshold used to
define the indicators (eg daily versus non-daily dependency). On the other hand, a set of
HSEs not surprisingly provides more information than does a single health-adjusted life
expectancy indicator. For example, contrasting trends may be found between LFLE and ILE,
or between ILE and ALE, which could well be of policy significance.
HLE (as a health-adjusted life expectancy indicator) overcomes these limitations, but
introduces new ones – namely, the validity of the preference weights (or equidistant weights)
for the non-fatal health states, and the more complex interpretation of the indicator as a
transformation rather than a decomposition of LE. Also, as stated above, the preference
weights are liable to be misunderstood as valuations of people’s lives.
If only a single indicator is to be selected – for reasons of policy focus and ease of use –
then ILE may be the best choice. Firstly, ILE does not require valuation of non-fatal health
states. Secondly, the functional limitation threshold used in the construction of ILE –
dependency – is both stable and meaningful in a policy sense. Finally, as a decomposition
rather than a transformation of LE, the LE-ILE difference and the ILE:LE ratio are directly
interpretable.
Whichever health expectancy indicator (or set of indicators) is chosen, they need to form
part of a ‘balanced scorecard’. Summary measures of population health such as health
expectancy should be seen as only one input into evidence-informed health policy, and need
to be supported by more detailed cause- and service-specific indicators. Nevertheless, this
metric can provide a powerful assessment of overall health system performance and may be
particularly valuable at the present time, as we enter an era of rapid structural ageing of the
population.
Recommendations
The following recommendations are addressed primarily to the Ministry of Health and
Statistics NZ.
1. Health expectancy should continue to be monitored as the ‘peak’ health system
outcome indicator, and reported in the Health and Independence Report (Ministry of
Health), The Social Report (Ministry of Social Development) and similar publications.
2. Only a single health expectancy indicator should be routinely reported and
monitored: independent life expectancy (ILE).
3. This indicator (ILE) should be considered for Tier 1 status as part of New Zealand’s
official statistics.
4. ILE should be monitored and reported five-yearly, in the second year following each
Census of Population and Dwellings.
5. Estimates should be produced (nationally) for both the total New Zealand and Mäori
populations.
30
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
6. The sources of data should continue to be the official life tables and the post-censal
disability survey (or equivalent survey), both provided by Statistics NZ.
7. Production of the ILE estimates from these data, using standard methods (ie those
set out in Appendix 1 of this report) as per the requirements for Tier 1 statistics, and
the reporting and interpretation of these estimates, should be the responsibility of the
Ministry of Health.
8. The Ministry of Health and Statistics NZ and should undertake further joint work to
develop methods for producing:
(a) projections of ILE
(b) subnational estimates of ILE (ie regional, ethnic, socio-economic group)
(c) improved ILE estimates and projections for Mäori.
9. Use and usefulness of ILE as a summary measure of population health, to inform the
Ministry of Health’s long-term planning as well as broader social policy, should be
periodically evaluated.
10. New Zealand, through the Ministry of Health, should participate actively in attempts
by the International Network on Health Expectancy (REVES) and other international
organisations to improve the cross-country comparability and international
benchmarking of health expectancy estimates.
31
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
References
Blakely, T, Tobias, M, Atkinson, J et al (2007). Tracking Disparity: Trends in ethnic and
socioeconomic inequalities in mortality, 1981–2004. Wellington: Ministry of Health.
Davis, P, Graham, P, & Pearce, N (1999). Health expectancy in New Zealand 1981–1991:
social variations and trends in a period of rapid social and economic change. Journal of
Epidemiology and Community Health. 53: 519–27.
European Health Expectancy Monitoring Unit (2007). Interpreting Health Expectancies.
EHEMU Reports. Montpellier: Author.
Graham, P, Blakely, T, Davis, P et al (2004). Compression, expansion or dynamic
equilibrium? The evolution of health expectancy in New Zealand. Journal of Epidemiology
and Community Health. 58: 659–66.
Health Funding Authority (1998). Disability in New Zealand. Wellington: Author.
Imai, K, Soneji, S (2007). On the estimation of disability-free life expectancy: Sullivan’s
method and its extension. Journal of the American Statistical Association. 102: 480 1199–
1211.
Jagger, C, Cox, B, & Le Roy, S (2006). Health Expectancy Calculation by the Sullivan
Method. Third Edition. Paris: European Union Health Expectancy Monitoring Unit.
Mathers, CD & Robine, JM (1997). How good is Sullivan’s method for monitoring changes in
population health expectancies? Journal of Epidemiology and Community Health. 51: 80–86.
Mathers, CD (2001). Healthy life expectancy in 191 countries. Lancet 357: 1685–91.
Ministry of Health (2003a). Health and independence report. Wellington: Author.
Ministry of Health (2003b). Statement of Intent. Wellington: Author.
Ministry of Health & Statistics New Zealand (2008). Health Expectancy: Toward Tier 1 official
statistic status. Wellington: Author.
Molla, MT, Wagener, DK & Madans, JH (2001). Summary measures of population health:
methods for calculating healthy life expectancy. Healthy People 2010 statistical notes.
Atlanta: Centers for Disease Control and Prevention (CDC).
Ministry of Social Development (2003). The Social Report 2003. Wellington: Author.
Murray, CJL, Salomon, JA, Mathers, CD et al (2002). Summary Measures of Population
Health. Geneva: World Health Organization.
Nusselder, WJ & Looman, C (2004). Decomposition of differences in health expectancy by
cause. Demography 41: 315–334.
Organization for Economic Cooperation and Development (2007). Health at a Glance 2007.
Paris: Author.
Parliamentary Office of Science and Technology (2006). Postnote: Healthy Life Expectancy.
London: Author.
32
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Rasulo, D (2007). Decomposition of changes in disability-free life expectancy by cause.
England, 1991–2001. Unpublished report. London: Office for National Statistics.
Romieu, I & Robine, JM (1997). Health Expectancies in OECD Countries. Paris: REVES
Statistics New Zealand (1998). Disability counts. Wellington: Author.
Statistics New Zealand (2002). Disability counts 2001. Wellington: Author.
Statistics New Zealand (2007). Hot Off The Press: 2006 Disability Survey. Wellington:
Author.
Statistics New Zealand (2008a). Principles and protocols for producers of Tier 1 statistics.
Available from: http://www.statisphere.govt.nz/about-official-statistics/principles-andprotocols-for-producers-of-tier1-statistics/default.htm.
Statistics New Zealand (2008b). Top down review of official statistics system. Available from:
http://www.stats.govt.nz/about-us/who-we-are/review-of-snz/top-down-review-official-statssystem.htm.
Stouthard, MEA, Essink-Bot, ML, Bonsel, GJ et al (1997). Disability weights for diseases in
the Netherlands. Rotterdam: Erasmus University Press.
Stouthard, MEA, Essink-Bot, ML & Bonsel, GJ (2000). Disability weights for diseases: a
modified protocol and results for a Western European region. European Journal of Public
Health 10: 24–30.
Sullivan, DF (1971). A single index of mortality and morbidity. HSMHA Health Reports 86:
347–54.
Tobias, M & Blakey, K (2007). Measuring health states. Wellington: Ministry of Health.
Tobias, M, Bryant, J, Teasdale, A, et al (2004). Population ageing and health expenditure:
New Zealand 2002–2051. Wellington: Ministry of Health.
Tobias, M & Cheung, J (1999). Independent life expectancy in New Zealand, 1996–97.
Australian Health Review 22: 78–91.
Tobias, M & Cheung, J (2004). Longer Life, Better Health? Trends in health expectancy,
New Zealand 1996–2001. Wellington: Ministry of Health.
Tobias, M, Salzano, S, & Rodway, P (2009). Long Term Health Expenditure Model.
Unpublished report. Ministry of Health.
World Health Organization (1997). The World Health Report 1997: Conquering suffering,
enriching humanity. Geneva: Author.
World Health Organization (2000). The World Health Report 2000: Health systems:
improving performance. Geneva: Author.
World Health Organization (2001). ICF: International Classification of Functioning, Disability
and Health. Geneva: Author.
World Health Organization (2002). The World Health Surveys. Geneva: Author.
World Health Organization (2003). Cross population comparability of evidence for health
policy. Discussion Paper 46. Geneva: Author.
33
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Appendix 1
Method for calculating health expectancies using Sullivan’s
observed prevalence approach
Given smoothed disability prevalence rates by support need level and five-year age group
(see Ministry of Health and Statistics New Zealand 2008), the ordinary abridged life table
can be converted into a Sullivan observed prevalence life table by inserting these rates into
column 10 of the spreadsheet as shown below. Calculation of health expectancy and its SE
then follows from the formulae embedded in the spreadsheet for columns 11 to 20.
A full explanation for these formulae is provided in the European Health Expectancy
Monitoring Unit manual (Jagger et al 2006), available at: www.ehemu.eu.
An example spreadsheet is shown below. Please note that the numbers used in this
example are merely illustrative, they are not the numbers used in the spreadsheets used to
produce the actual estimates presented in this report.
Explanation of columns in example spreadsheet
Column no.
Explanation
1 to 9
abridged life table supplied by Statistics NZ
10
disability rates (in this report the smoothed disability prevalence rates from the
2006 post-censal Disability Survey)
13
column 12 / column 2, ie, HEx = ∑[(1-πx)×Lx] / lx
14
total number of participants in the age interval in the 2006 post-censal
Disability Survey
15
= [column 10×(1–column 10)] / column 14, ie, S2(πx) = [πx×(1– πx)] / Nx
18
= column 17 / (column 2)2 , ie, S2(HEx) = ∑L2 S2(πx) / (lx)2
19
= square root of column 18, ie, S(HEx) = √S2(HEx)
20 and 21
= column 13 ± 1.96 × column 19
Note: the term ‘disability rate’ is used here as a convenient label for the more correct ‘functional
limitation rate’
34
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Example health expectancy spreadsheet
1
2
3
4
Out of 100,000 people born:
Exact
age
(years)
x
0
1
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
5
6
Probability that a
person who reaches
this age:
7
8
9
10
11
12
13
Proportion
of
age group
x to x+5
surviving
another
five years
Expected
number of
years
of life
remaining
at age x
Proportion
of age
group
with
disability
Person
years
lived
without
disability
in interval
Total
years
lived
without
disability
from age x
Health
expectancy
(LFLE, ALE,
or ILE)
sx
0.99897
…
0.99941
0.99763
0.99547
0.99493
0.99505
0.99467
0.99298
0.98958
0.98439
0.97609
0.96201
0.93864
0.90097
0.83978
0.74359
0.59447
…
ex
78.1
77.5
73.6
68.7
63.7
59.0
54.2
49.5
44.7
40.0
35.3
30.7
26.3
22.0
18.0
14.3
10.9
8.0
5.6
πx
0.101249
0.101249
0.103957
0.103227
0.097627
0.092859
0.095236
0.104259
0.118193
0.1394
0.172587
0.219576
0.277406
0.336744
0.390849
0.442037
0.490588
0.529187
0.552611
(1- πx)*Lx
89481.49
357468
445143.8
445245.3
446962.5
447288.7
443856.8
437255.1
428158.9
414926.8
394769.7
366537.2
331260.5
292506.2
252160.2
208098.2
159550.7
109649.8
94110.85
Σ[(1- πx)*Lx]
6164430.892
6074949.399
5717481.42
5272337.613
4827092.305
4380129.806
3932841.073
3488984.276
3051729.205
2623570.263
2208643.491
1813873.745
1447336.507
1116075.998
823569.7939
571409.5832
363311.3706
203760.6949
94110.85054
HEx
61.6
61.1
57.5
53.1
48.6
44.3
40.0
35.6
31.3
27.1
23.0
19.1
15.6
12.4
9.6
7.2
5.2
3.7
2.5
Number
alive
at
exact age
Average
number
alive in
the age
interval
Number
dying
in
the age
interval
Is alive
at end of
the age
interval
Dies in
the age
interval
Central
annual
death
rate
for
the age
interval
lx
100,000
99,491
99,388
99,336
99,231
98,861
98,363
97,873
97,384
96,811
95,992
94,776
92,973
90,205
85,895
79,247
69,326
55,278
37,356
Lx
99,562
397,738
496,788
496,497
495,319
493,075
490,578
488,149
485,547
482,136
477,113
469,664
458,433
441,016
413,954
372,961
313,205
232,895
210,356
dx
509
103
51
106
370
498
490
489
573
819
1,216
1,803
2,769
4,310
6,647
9,921
14,048
17,922
37,356
px
0.99491
0.99896
0.99949
0.99893
0.99627
0.99496
0.99502
0.99500
0.99412
0.99154
0.98733
0.98098
0.97022
0.95222
0.92261
0.87480
0.79737
0.67579
0.00000
qx
0.00509
0.00104
0.00051
0.00107
0.00373
0.00504
0.00498
0.00500
0.00588
0.00846
0.01267
0.01902
0.02978
0.04778
0.07739
0.12520
0.20263
0.32421
1.00000
mx
0.00511
0.00026
0.00010
0.00021
0.00075
0.00101
0.00100
0.00100
0.00118
0.00170
0.00255
0.00384
0.00605
0.00979
0.01610
0.02671
0.04510
0.07739
0.40000
Notes: Numbers are for illustration only, the data is not real. The sample spreadsheet continues on the next page.
35
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
14
15
16
17
Number
in
survey
in age
interval
Nx
120
300
350
345
412
535
458
654
752
851
1024
1125
521
475
532
402
325
216
1254
S2(πx)
0.000758
0.000303
0.000266
0.000268
0.000214
0.000157
0.000188
0.000143
0.000139
0.000141
0.000139
0.000152
0.000385
0.00047
0.000448
0.000614
0.000769
0.001153
0.000197
L2S2(πx)
7516824
47984635
65683502
66144033
52459950
38280139
45278098
34027088
32674632
32769758
31744758
33599918
80858129
91452603
76687680
85342172
75432902
62563872
8724001
ΣL2S2(πx)
969224693
961707870
913723235
848039732
781895699
729435749
691155610
645877513
611850425
579175793
546406035
514661277
481061360
400203230
308750627
232062947
146720775
71287873
8724001
18
19
20
21
Variance of
HE
Standard
error of
HE
Lower
95% CI of
HE
Upper
95% CI of
HE
S(HEx)
0.31
0.31
0.30
0.29
0.28
0.27
0.27
0.26
0.25
0.25
0.24
0.24
0.24
0.22
0.20
0.19
0.17
0.15
0.08
LCI(HEx)
61.0
60.4
56.9
52.5
48.1
43.8
39.5
35.1
30.8
26.6
22.5
18.7
15.1
11.9
9.2
6.8
4.9
3.4
2.4
UCI(HEx)
62.3
61.7
58.1
53.7
49.2
44.8
40.5
36.2
31.8
27.6
23.5
19.6
16.0
12.8
10.0
7.6
5.6
4.0
2.7
2
S (HEx)
0.096922469
0.097157331
0.092501872
0.085940625
0.079406713
0.074634573
0.071435486
0.06742611
0.064516946
0.061796112
0.059298569
0.057296093
0.055652635
0.049184027
0.041848225
0.036951914
0.030528187
0.02332975
0.006251501
Note: Numbers are for illustration only, the data is not real.
36
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Appendix 2
Summary of feedback from consultation on discussion document
The consultation process sought comment and feedback from various stakeholders,
including experts in the field, central and local governments, health sector organisations and
other potential users of health expectancy estimates and projections. The discussion paper
Health Expectancy: Toward Tier 1 official statistic status (Ministry of Health and Statistics
New Zealand 2008) was widely circulated and the opportunity for stakeholders to comment
was invited via a feedback form attached to the end of the report
The questions asked in this feedback form were:
1.
2.
3.
4.
5.
6.
7.
8.
Do you favour a single health expectancy indicator, or set of indicators?
Should they be Tier 1?
How often should they be updated?
Should estimates continue to be produced nationally?
Where do you think the source data should come from?
How do you feel about the proposed method for calculating health expectancy?
How should the results be presented?
What should health expectancy estimates and projections be used for? Why is it
necessary to have this information?
9. Any other comments?
The paper was well received by most stakeholders and valuable feedback was provided by
some. In addition, three meetings were held to elicit further comment and provide an
opportunity for more detailed debate: one with Ministry of Health policy analysts, one with
senior Statistics New Zealand advisors, and one with a senior representative of the Office of
Disability Issues. A summary of the responses to the discussion paper, both written and oral
(ie via the three meetings) is provided in the table below.
The feedback obtained through this consultation process has helped shape the current
report, including the final recommendations set out in the report, and so will contribute to the
future of health expectancy as an outcome measure for health system performance
assessment in New Zealand. We are grateful to all those who provided feedback.
37
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Summary of feedback received via the consultation process on the discussion document
Note: Although we have tried to accurately reflect stakeholders’ views, this cannot always be guaranteed in a summary table.
Question
MOH (Public Health )
NZ Nurses Organisation
Christchurch City Council
Should not yet be Tier 1, until more
familiarity
Supports Tier 1
Not Tier 1 as it doesn’t meet
requirements
Preferably one indicator, but no
preference as to which
Favours a small set of indicators
(each giving different information)
Recommends publicity/education
re. ILE (otherwise use small set).
Supports one indicator (not specific
as to which one)
How often do you
think health
expectancy
indicators should
be updated?
Supports regular collection for
consistent time series
Regular updates (after each
census). Recommends values
survey every 10-20 years to
determine health state weights for
calculation of HLE
Five-yearly updating
Five-yearly updating
Do health
expectancy
estimates need to
be produced
subnationally?
Recommends cohort analysis be
added
Subnational estimates
(ethnic/regional)
Subnational estimates (especially
Mäori and rural)
Subnational estimates, especially
geographic (TLA), also
ethnic and deprivation
Uses of health expectancy
indicators – policy, workforce
planning, programme evaluation,
debates on ethical issues, eg
quality and end-of-life decision
making, resource allocation in
relation to population ageing
Supports existing data sources
Should health
expectancy be
recognised as a
Tier 1 statistic?
Do you favour one
single health
expectancy
indicator or a set
of indicators?
Waikato University
(Demography)
Should be Tier 1
Other comments
38
Uses of health expectancy indicators
should include measuring community
progress
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Question
Should health
expectancy be
recognised as a Tier 1
statistic?
University of Auckland (Public Health)
Supports Tier 1
MOH (Information Directorate)
Not Tier 1 – wants international benchmarks
established first
MOH (Policy group)
Supports Tier 1
Do you favour one single
health expectancy
indicator or a set of
indicators?
Single indicator - ILE
One indicator - ILE
One indicator - ILE
How often do you think
health expectancy
indicators should be
updated?
Five-yearly updates
No comment
Five-yearly updates
Do health expectancy
estimates need to be
produced subnationally?
Subnational estimates (Mäori and non-Mäori)
Subnational (Mäori, Pacific and deprivation)
Subnational estimates (Mäori, Pacific,
Asian, essential - recommends partial (eg
0-85) HE, if full HE (0-100+) not possible
for smaller ethnic groups
Other comments
Uses of health expectancy indicators –
research/policy
HLE problematic, unless we can get good
health state valuations for NZ
Non-fatal outcomes not adequately captured
– aspects of wellbeing excluded (eg ‘good’
death)
39
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Question
Auckland Regional Public Health Service
MOH (Mäori, Pacific)
Office of Disability Issues
Should health expectancy
be recognised as a Tier 1
statistic?
Supports Tier 1, but with a commitment to stable,
long-term measuring
Supports Tier 1 – which would help to
achieve international comparability of health
expectancy indicators
Unsure, as it could be subject to change
Do you favour one single
health expectancy
indicator or a set of
indicators?
Both indicators – ILE and HLE
Single indicator - ILE
It is essential to make the case as to why
we have to move away from current
mortality measures of health
How often do you think
health expectancy
indicators should be
updated?
Five-yearly updates
Five-yearly updates
No comment
Do health expectancy
estimates need to be
produced subnationally?
Producing sub-national estimates have limitations
and may not prove useful. Rather, we would like
focus to be on those indicators which contribute to
the functioning and delivery of public health
services
Health expectancy estimates (total New
Zealand and Mäori populations, Pacific
population – suggest small domain estimates
and partial health expectancy (0–84 yrs)
estimates, Asian population, different age
groups, especially children (0–6 yrs))
No comment
40
Longer Life, Better Health? Trends in health expectancy in New Zealand, 1996–2006
Other comments
As proposed at a regional level, envisage no uses
for the health expectancy indicators. Central
agencies may be able to use high level statistics
with regard to trends
Relative calculations that use the three health
state expectancy measures could lead to
inaccurate assessments of health disparities
between Mäori and non-Mäori. Recommend
reporting only one measure
Uses of health expectancy indicators –
provide understandable and accessible
measure of health outcomes/improvements
over time, highlighting differences, costs of
long-term conditions, and addressing
inequalities. To forecast ahead and estimate
impact of an ageing population, monitor
health system performance, comparison with
other countries
Ethical issues need to be clarified,
including differentiating ‘disability’ from
‘impairment’ (functional limitation), and
making clear that health state valuations
used in HLE are not valuing people’s lives
The key point is that disability depends on
the environment - the services available
to people with impairments, access to
support, structural modifications to the
environment etc
Non-fatal health outcomes should
therefore be defined in terms of
impairment or functional limitation, not
disability
41